CAJ | 학술논문

文章针对传统的非局部均值算法只关注图像几何结构信息而忽略图像的方向结构信息，提出了一种基于增强邻域结构方向信息的非局部均值算法。通过增强邻域结构方向信息能够更加合理地描述邻域间的相似度，使相似度高的邻域获得更高的权重，相似性度量也具有较强的鲁棒性。实验结果表明，算法能够取得很好的去噪效果，同时能够保留图像的边缘结构信息，特别在结构比较复杂的区域体现得更加明显。
문장침대전통적비국부균치산법지관주도상궤하결구신식이홀략도상적방향결구신식，제출료일충기우증강린역결구방향신식적비국부균치산법。통과증강린역결구방향신식능구경가합리지묘술린역간적상사도，사상사도고적린역획득경고적권중，상사성도량야구유교강적로봉성。실험결과표명，산법능구취득흔호적거조효과，동시능구보류도상적변연결구신식，특별재결구비교복잡적구역체현득경가명현。
As traditional non‐local mean value algorithm only concerns about geometric structural infor‐mation of the image w hile ignores the directional structural information ,a new non‐local mean value algorithm based on directional information of enhanced neighboring structure is proposed .The simi‐larity between the neighbor fields can be described more reasonably by directional information of en‐hanced neighboring structure .It makes more similar neighborhoods obtain higher weights and the measurement of similarity is more robust .The experimental results show that the new algorithm a‐chieves good denoising effect and reserves marginal information simultaneously .The result is much better especially in the area w here structure is more complicated .